[184 Pages Report] The AI in manufacturing market is expected to grow from USD 1.0 billion in 2018 to USD 17.2 billion by 2025, at a CAGR of 49.5% during the forecast period. The huge availability of big data and increase in venture captital investments are the factors fueling the growth of the AI in manufacturing market. In addition, evolving industrial IoT and automation is further supplementing the growth of the AI in manufacturing market.

Processor to hold largest market in hardware segment

Increasing need for hardware platforms with high computing power to run various AI software is the key factor accelerating the growth for hardware devices in the AI in manufacturing market. Demand for high-computing processors to run AI algorithms continues to surge its growth in the hardware segment. The processor segment consists of MPUs, GPUs, FPGAs, and ASICs. In processors, GPUs are expected to foresee strong growth owing to high parallel computing capabilities, and the same is expected to continue in the coming years.

Machine learning to witness higher growth during forecast period

Machine learning’s ability to collect and handle big data and its applications in various manufacturing applications such as predictive analytics and machinery inspection, quality control, and cybersecurity are fueling its growth. Moreover, ML is expected to account for the largest share of the AI in manufacturing market throughout the forecast period. This is attributed to the enormous availability of data, also called big data, and increase in adoption of ML by factories to improve productivity, reduce machine downtime, and reduce operational cost.

Predictive maintenance and machinery inspection to hold largest size of AI in manufacturing market

Extensive use of computer vision and machine learning technology for machinery inspection, installation of Industrial IoTs, and usage of big data in the manufacturing industry are the factors driving the growth of predictive maintenance and machinery inspection in the AI in manufacturing market. The predictive maintenance and machinery inspection is a regular and systematic application of AI, which ensures proper functioning of equipment and reduces its rate of deterioration. The AI technology in predictive maintenance and machinery inspection encompasses regular examination, inspection, lubrication, testing, and adjustments of equipment without prior knowledge of equipment failure.

APAC to account for significant share followed by North America in AI in manufacturing market during forecast period

APAC is also considered to have the most number of manufacturing plants in the world. There are a few dark plants in China, where only robots works, and no human is required. AI implementation can make robots smarter, reduce the downtime of machines, and increase the productivity. Hon Hai Precision Industry Co., Ltd (China) replaced 60,000 factory workers by robots in 2016. This high rate of adoption of industrial robots in manufacturing plants is expected to drive the growth of the AI in manufacturing market in APAC. North America is the major contributor in the AI in manufacturing market, wherein the US accounted for the largest share in 2017. Cross-industry participation in the manufacturing domain, along with a significant increase in venture capital investment, has further propelled the growth of the AI in manufacturing market in North America.

Key Market Players

A few companies in the AI in manufacturing market are NVIDIA (US), Intel (US), IBM (US), Google (US), Microsoft (US), AWS (US), General Vision (US), GE (US), Siemens (Germany), and Mitsubishi Electric (Japan). The market has active participation of start-ups. A few emerging start-ups in the market are AIBrain (US), Ubtech Robotics (China), and Darktrace (UK).

Intel is among the market leaders in designing and manufacturing advanced integrated digital technology platforms. The company has robust market presence, especially in the PC and data center market, and invests significantly in R&D, which has resulted in its strong position in the AI market. The company has computing solutions for large complex applications in the cloud to small low-power mobile devices at the edge. In the past 2 years, Intel has significantly demonstrated its strong inorganic growth strategy. The acquisition of companies such as Saffron Technology, Altera, Nervana Systems, Movidius, and Mobileye has further improved its AI product portfolio. As a result, Intel launched a few major products catering to AI, ML, and DL (neural networking). Moreover, a partnership with AI software solution and service providers is expected to remain a vital growth strategy of the company in the coming years.

Recent Developments

In September 2018, Siemens launched a new service approach for overhead line inspection called "SIEAERO" at European Utility Week 2018 in Vienna, Austria. For the first time, AI and a long-range unmanned aerial vehicle (UAV) are used to inspect transmission lines. SIEAERO smart analytics software utilizes AI and ML to store, manage, and analyze all data in one integrated software system.

In September 2018, Shell Global Solutions (US) announced that it is broadening its work with Microsoft to help accelerate industry transformation and innovation. Through this collaboration, Shell will drive efficiencies across the company from drilling and extraction to employee empowerment and collaboration, as well as safety for its retail customers and employees. As part of this deal, Shell announced that it has selected C3 IoT with Microsoft Azure as its AI platform to enable and accelerate digital transformation on a global scale.

In March 2018, Siemens and Atos announced the reinforcement of their strategic cooperation, with plans to accelerate their joint business until 2020 through an ambitious joint go-to-market plan and the strengthening of their joint innovation and investment program. The program has been increased by ~USD 107 million (€100 million), totaling ~USD 353 million (€330 million)—more than three times the original sum.

Key questions addressed in the report

Which are the major applications of AI in manufacturing market? How big is the opportunity for their growth in the developing economies in the next 5 years?

Which are the major companies in the AI in manufacturing market? What are their major strategies to strengthen their market presence?

Which AI technology will find its major application in manufacturing?

Which are the leading countries in the AI in manufacturing market? What would be the share of North America and Europe in this market in the next 5 years?

What will be the role of the standards and regulations by governments and associations in the adoption of AI in manufacturing?

To speak to our analyst for a discussion on the above findings, click Speak to Analyst

6 Artificial Intelligence in Manufacturing Market, By Offering (Page No. - 51) 6.1 Introduction 6.2 Hardware 6.2.1 Processor 6.2.1.1 MPU 6.2.1.1.1 MPUs to Hold the Largest Share of AI in Manufacturing Market for Processors During the Forecast Period 6.2.1.2 GPU 6.2.1.2.1 GPUs to Grow at the Highest CAGR During the Forecast Period 6.2.1.3 FPGA 6.2.1.3.1 Low Power Consumption and Low Latency Expected to Drive the Market for FPGA 6.2.1.4 Asic 6.2.1.4.1 User-Specific Customized Solution Offered By Asic to Drive Its Market 6.2.2 Memory 6.2.2.1 High-Bandwidth Memory is Being Developed and Deployed for AI Applications, Independent of Its Computing Architecture 6.2.3 Network 6.2.3.1 Nvidia (US), Intel (US) and Mellanox Technologies (Israel) are the Key Providers of Network Interconnect Adapters for AI Applications 6.3 Software 6.3.1 AI Solutions 6.3.1.1 On-Premises 6.3.1.1.1 Data-Sensitive Enterprises Prefer On-Premise Advanced Nlp and Ml Tools to Be Used in AI Solutions 6.3.1.2 Cloud 6.3.1.2.1 AI Solution Providers are Focusing on the Development of Robust Cloud-Based Solutions for Their Clients 6.3.2 AI Platform 6.3.2.1 Machine Learning Framework 6.3.2.1.1 Major Tech Companies Such as Google, IBM, and Microsoft are Developing and Offering Their Own Ml Frameworks 6.3.2.2 Application Program Interface (API) 6.3.2.2.1 An API Provides A Platform for A Set of Routines and Tools for Building Software Applications 6.4 Services 6.4.1 Deployment & Integration 6.4.1.1 Deployment and Integration is A Key Service Required for Configuring AI Systems in Manufacturing 6.4.2 Support & Maintenance 6.4.2.1 The Ultimate Objective of Maintenance Services is to Keep the System at an Acceptable Standard

8 Artificial Intelligence in Manufacturing Market, By Application (Page No. - 75) 8.1 Introduction 8.2 Predictive Maintenance and Machinery Inspection 8.2.1 Predictive Maintenance and Machinery Inspection Provide the Framework for All Planned Maintenance Activities 8.3 Material Movement 8.3.1 AI-Based Technology for Material Movement Will Ensure Streamlining of In-Plant Logistics 8.4 Production Planning 8.4.1 The Use of AI in Production Planning Leads to the Standardization of Product and Process Sequence 8.5 Field Services 8.5.1 Field Services are Extensively Used in Heavy Metals and Machine Manufacturing, Oil & Gas, and Energy and Power Industry 8.6 Quality Control 8.6.1 AI-Based Quality Control System is Widely Used in Pharmaceuticals, Food & Beverages, and Semiconductor Industries 8.7 Cybersecurity 8.7.1 Automation and Integrating Real-Time Systems in Manufacturing is Resulting in Adoption of Cybersecurity Systems 8.8 Industrial Robots 8.8.1 Industrial Robots Can Be Classified Into Traditional Industrial Robots and Collaborative Robots 8.9 Reclamation 8.9.1 in Reclamation, AI-Based Systems Detect Important Components From Waste Or Slags

9 Artificial Intelligence in Manufacturing Market, By Industry (Page No. - 92) 9.1 Introduction 9.2 Automobile 9.2.1 Machine Learning and Computer Vision are the Major AI Technologies Deployed in Automobile Industry 9.3 Energy and Power 9.3.1 AI-Based Solutions Can Help Energy and Power Industry to Enhance Production Output and Reduced Downtime 9.4 Pharmaceuticals 9.4.1 Quality Control, Material Movement, and Production Planning are the Major Applications of AI in Pharmaceuticals 9.5 Heavy Metals and Machine Manufacturing 9.5.1 APAC is Considered to Have the Highest Number of Heavy Metals and Machine Manufacturing Plants in the World 9.6 Semiconductors and Electronics 9.6.1 AI is Likely to Assist in Optimizing the Production Cost, Technology Implementation, and Integration of Components 9.7 Food & Beverages 9.7.1 AI-Based Solutions Enhance the Quality of the Food Production Cost-Effectively 9.8 Others

10 Artificial Intelligence in Manufacturing Market, By Region (Page No. - 103) 10.1 Introduction 10.2 North America 10.2.1 US 10.2.1.1 US is Among the Frontrunners in Terms of Adoption of Iiot and Industrial Robots Which is Boosting the Adoption of AI 10.2.2 Canada 10.2.2.1 Government Funding and Extensive Start-Up Activity, Especially in AI are the Major Factors Supporting the Growth of AI 10.2.3 Mexico 10.2.3.1 Increase the Productivity and Reduce the Cost are the Major Factors Leading to the Adoption of AI in Mexico 10.3 Europe 10.3.1 Germany 10.3.1.1 Implementation of Big Data in the Manufacturing Plant has Resulted in the Adoption of AI-Based Solutions in Germany 10.3.2 UK 10.3.2.1 Favorable Environment for R&D has Led to Innovations in the Field of AI in Manufacturing 10.3.3 France 10.3.3.1 Increased Funding and Rising AI Start-Ups are Expected to Proliferate AI in France 10.3.4 Italy 10.3.4.1 Manufacturers in Italy are Adopting Smart Factory and AI-Based Solutions 10.3.5 Spain 10.3.5.1 Cybersecurity is Among the Emerging Trend of AI in the Manufacturing Sector in Spain 10.3.6 Rest of Europe 10.4 APAC 10.4.1 China 10.4.1.1 Manufacturing Sectors in China are Growing Rapidly, Resulting in the Introduction of New Robotics and Big Data Technologies 10.4.2 Japan 10.4.2.1 Federal Initiatives and Presence of World-Leading Manufacturing Companies is Expected to Boost AI in Japan 10.4.3 South Korea 10.4.3.1 Quality Manufacturing Services and Introduction of Automation in Manufacturing Industries is Driving the Market of AI in South Korea 10.4.4 India 10.4.4.1 AI in the Manufacturing Industry is Still in Its Nascent Stage in India 10.4.5 Rest of APAC 10.5 RoW 10.5.1 South America 10.5.1.1 South American Region Invests Heavily in IT Services 10.5.2 Middle East and Africa 10.5.2.1 Growing Manufacturing Expenditure in Israel, the Middle East, and North Africa is A Key Growth Driver of AI in Manufacturing

Figure 1 Artificial Intelligence in Manufacturing Market: Research DesignFigure 2 Market Size Estimation Methodology: Bottom-Up ApproachFigure 3 Market Size Estimation Methodology: Top-Down ApproachFigure 4 Data TriangulationFigure 5 Assumptions for the Research StudyFigure 6 AI in Manufacturing Market, By Offering, 2018 vs 2025 (USD Million)Figure 7 AI in Manufacturing Market, By Technology, 2015–2025 (USD Million)Figure 8 AI in Manufacturing Market, By Application, 2018 vs 2025 (USD Million)Figure 9 AI in Manufacturing Market, By Industry, 2018 vs 2025 (USD Million)Figure 10 AI in Manufacturing Market, By Region, 2018Figure 11 Growing Big Data in Manufacturing and Increasing Industrial Automation are Major Factors Driving Market GrowthFigure 12 Software to Hold Largest Share of AI in Manufacturing Market During Forecast PeriodFigure 13 AI in Manufacturing Market for Machine Learning to Hold Largest Size From 2018 to 2025Figure 14 China to Hold Largest Share of AI in Manufacturing Market in 2018 in APACFigure 15 US to Hold Largest Share of AI in Manufacturing Market in 2018Figure 16 Increasingly Large and Complex Data Set and Industry Trends Such as IoT and Automation are Driving Market GrowthFigure 17 AI in Manufacturing Market Value Chain in 2017Figure 18 Software to Hold Largest Size of AI in Manufacturing Market During Forecast PeriodFigure 19 Market for GPU to Grow at Highest CAGR During Forecast PeriodFigure 20 APAC to Hold Largest Size of AI in Manufacturing Market for Software From 2018 to 2025Figure 21 Machine Learning to Hold Largest Market Share of AI in Manufacturing Market in 2018 and 2025Figure 22 Quality Control to Witness Highest Growth Throughout Forecast PeriodFigure 23 North America to Hold Largest Share of AI in Manufacturing Market for Material Movement in 2018Figure 24 North America to Hold Largest Size of AI Manufacturing Market for Field Services During Forecast PeriodFigure 25 Machine Learning to Hold Largest Size of AI in Manufacturing Market for Application of Quality Control During 2018–2025Figure 26 APAC to Hold Largest Share of AI in Manufacturing Market for Application of Industrial Robots During 2018–2025Figure 27 Automobile Held Largest Size of AI in Manufacturing Market in 2018Figure 28 APAC to Hold Largest Size of AI in Manufacturing for Energy and Power By 2025Figure 29 APAC to Hold Largest Size of AI in Manufacturing Market for Heavy Metals and Machine Manufacturing During Forecast PeriodFigure 30 China & US are Emerging as New Hot Spots in AI in Manufacturing MarketFigure 31 APAC to Dominate AI in Manufacturing Market During Forecast PeriodFigure 32 North America: Snapshot of AI in Manufacturing MarketFigure 33 Europe: Snapshot of AI in Manufacturing MarketFigure 34 Germany Held Largest Share of AI in Manufacturing Market in Europe for Hardware in 2018Figure 35 APAC: Snapshot of AI in Manufacturing MarketFigure 36 RoW: Snapshot of AI in Manufacturing MarketFigure 37 Key Developments Adopted By Top Players in AI in Manufacturing Market From 2016 to 2018Figure 38 Ranking of Key Companies in AI in Manufacturing Market (2017)Figure 39 Battle for Market Share: Product Launch Was Key Growth Strategy From 2016 to 2018Figure 40 Nvidia: Company SnapshotFigure 41 Intel: Company SnapshotFigure 42 IBM: Company SnapshotFigure 43 Siemens: Company SnapshotFigure 44 GE: Company SnapshotFigure 45 Google: Company SnapshotFigure 46 Microsoft: Company SnapshotFigure 47 Micron Technology: Company SnapshotFigure 48 AWS: Company Snapshot

The study involved 4 major activities in estimating the current size of the AI in manufacturing market. Exhaustive secondary research has been conducted to collect information about the market, the peer market, and the parent market. Validating findings, assumptions, and sizing with industry experts across the value chain through primary research has been the next step. Both, top-down and bottom-up approaches have been employed to estimate the complete market size. In the subsequent steps, market breakdown and data triangulation methods have been used to estimate the market size of segments and subsegments.

Secondary Research

The research methodology used to estimate and forecast the AI in manufacturing market begins with capturing data on revenues of the key vendors in the market through secondary research. This study involves the use of extensive secondary sources, directories, and databases such as Hoovers, Bloomberg Businessweek, Factiva, and OneSource to identify and collect information useful for the technical and commercial study of the AI in manufactuing market. Moreover, secondary sources include annual reports, press releases, and investor presentations of companies; white papers, certified publications, and articles from recognized authors; directories; and databases. Secondary research has been mainly done to obtain key information about the industry’s supply chain, the market’s value chain, the total pool of key players, market classification and segmentation according to industry trends, geographic markets, and key developments from both market- and technology-oriented perspectives.

Primary Research

In the primary research process, various primary sources from both supply and demand sides were interviewed to obtain the qualitative and quantitative information relevant to AI in manufacturing market. Primary sources from the supply side include experts such as CEOs, vice presidents, marketing directors, technology and innovation directors, application developers, application users, and related executives from various key companies and organizations operating in the ecosystem of the AI in manufacturing market.

Market Size Estimation

Both, top-down and bottom-up approaches have been used to estimate and validate the overall size of the AI in manufacturing market. These methods have also been used extensively to estimate the size of various market subsegments. The research methodology used to estimate the market size includes the following:

Key players in major applications and markets have been identified through extensive secondary research.

The industry’s supply chain and market size, in terms of value, have been determined through primary and secondary research processes.

All percentage shares, splits, and breakdowns have been determined using secondary sources and verified through primary sources.

Data Triangulation

After arriving at the overall market size using the estimation processes as explained above, the market was split into several segments and subsegments. To complete the overall market engineering process and arrive at the exact statistics of each market segment and subsegment, data triangulation and market breakdown procedures have been employed, wherever applicable. The data have been triangulated by studying various factors and trends from both demand and supply sides.

Report Objectives

To describe and forecast the artificial intelligence (AI) in manufacturing market, in terms of value, by offering, technology, application, and industry

To describe and forecast the AI in manufacturing market, in terms of value, by region-North America, Europe, Asia Pacific (APAC), and Rest of the World (RoW)

To strategically analyze micromarkets with respect to individual growth trends, prospects, and contributions to the total market

To profile key players and comprehensively analyze their market position in terms of ranking and core competencies, along with detailing competitive landscape for market leaders

To analyze the competitive developments such as joint ventures, collaborations, agreements, contracts, partnerships, mergers & acquisitions, new product developments, and research and development (R&D) in the AI in manufacturing market